WO2021243898A1 - 数据分析方法、装置、电子设备及存储介质 - Google Patents

数据分析方法、装置、电子设备及存储介质 Download PDF

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Publication number
WO2021243898A1
WO2021243898A1 PCT/CN2020/118406 CN2020118406W WO2021243898A1 WO 2021243898 A1 WO2021243898 A1 WO 2021243898A1 CN 2020118406 W CN2020118406 W CN 2020118406W WO 2021243898 A1 WO2021243898 A1 WO 2021243898A1
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data
target
identifier
collection
request
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PCT/CN2020/118406
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English (en)
French (fr)
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刘明磊
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北京旷视科技有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/285—Clustering or classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/55—Clustering; Classification

Definitions

  • the present invention relates to the field of data processing technology, in particular to a data analysis method, device, electronic equipment and storage medium.
  • multiple data belonging to the same set may belong to different events, and the data of the same event may belong to different sets, making it impossible to analyze information related to the same event.
  • embodiments of the present invention are proposed to provide a data analysis method, device, electronic device, and storage medium that overcome the above-mentioned problems or at least partially solve the above-mentioned problems.
  • a data analysis method including:
  • the data classification request includes a data identifier corresponding to the data to be classified into the target data set and a target collection identifier corresponding to the target data set;
  • the data corresponding to the data identification is classified into a target data set corresponding to the target set identification, and the target data set includes a plurality of data associated with a target event;
  • a data analysis device including:
  • a classification request receiving module configured to receive a data classification request, where the data classification request includes the data identifier corresponding to the data to be classified into the target data set and the target collection identifier corresponding to the target data set;
  • the data categorization module is configured to categorize the data corresponding to the data identifier into the target data set corresponding to the target set identifier according to the data categorization request, and the target data set includes information associated with the target event Multiple data;
  • An analysis request receiving module configured to receive an analysis request for the target set identifier
  • the data analysis module is used to obtain multiple data corresponding to the target set identifier, and analyze the multiple data according to the analysis method in the analysis request to obtain the analysis result.
  • an electronic device including:
  • a memory in which computer-readable codes are stored
  • One or more processors when the computer-readable code is executed by the one or more processors, the computing processing device executes the data analysis method as described in the first aspect.
  • a computer program including computer-readable code, which when the computer-readable code runs on a computing processing device, causes the computing processing device to execute as described in the first aspect.
  • a computer-readable medium in which the computer program as described in the fourth aspect is stored.
  • the data corresponding to the data identifier is classified into the target data set corresponding to the target set identifier by receiving the data categorization request including the data identifier and the target set identifier
  • the target data set includes multiple data associated with the target event, receives an analysis request for the target set identifier, obtains multiple data corresponding to the target set identifier, and performs analysis on the multiple data according to the analysis method in the analysis request. Analyze and obtain the analysis result.
  • the problem of not being able to collect the data of a target event can be solved, and it can be based on multiple data in the target data set. Analyze the target event and realize the multi-dimensional analysis of the target event.
  • Figure 1 is a flow chart of the steps of a data analysis method provided by an embodiment of the present invention
  • Figure 2 is a flow chart of the steps of a data analysis method provided by an embodiment of the present invention.
  • Fig. 3 is a structural block diagram of a data analysis device provided by an embodiment of the present invention.
  • Fig. 4 schematically shows a block diagram of an electronic device for performing the method according to the present invention.
  • Fig. 5 schematically shows a storage unit for holding or carrying program codes for implementing the method according to the present invention.
  • Fig. 1 is a flow chart of the steps of a data analysis method provided by an embodiment of the present invention, which may be executed by an electronic device. As shown in Fig. 1, the method may include:
  • Step 101 Receive a data categorization request, where the data categorization request includes a data identifier corresponding to the data to be categorized into a target data set and a target set identifier corresponding to the target data set.
  • the data collection request is issued by the current user from the thread data display page or from the track tracking result display page.
  • the thread data display page displays thread data that the current user has added to the thread database.
  • Trajectory tracking is a process of retrieving data associated with multiple data corresponding to the target collection identifier from the data source obtained by the server according to the current user's trajectory tracking request for the target collection identifier. It is understandable that the multiple data corresponding to the target set identifier may be picture data, and the retrieval of data associated with the multiple data corresponding to the target set identifier may be based on the picture data. Picture data whose relationship meets preset conditions.
  • the receiving data categorization request includes: displaying a plurality of thread data corresponding to the current user on the thread data display page; receiving the data that the current user assigns the specified thread data to the target set identifier Included in the collection request.
  • the multiple clue data corresponding to the current user is the data that the current user has added to the clue database.
  • the clue data includes at least one of a camera capture result, a file capture result, a camera warning result, a video recording warning result, a file warning result, and a local associated picture.
  • the locally associated picture may be a picture saved in the user terminal.
  • the thread data corresponding to the current user is obtained from the thread database, and multiple thread data corresponding to the current user are displayed on the thread data display page.
  • Each thread data can be displayed with a grouping button.
  • the grouping button receives the data grouping request of the current user. If the current user's click operation of the grouping button for the specified clue data is detected, the data collection ID of the existing data collection is displayed, and the data collection selected by the user is obtained.
  • the identifier is used as the target collection identifier, so that a request for the current user to assign the specified clue data to the target collection identifier is received.
  • the data set identifier may include the data set name and/or the data set ID.
  • the receiving data categorization request includes: receiving a trajectory tracking request for a target set identifier; acquiring a trajectory tracking result, the trajectory tracking result being obtained from the server according to the trajectory tracking request Other data associated with the plurality of data corresponding to the target set identifier retrieved in the database; display the trajectory tracking result; receive the data categorization request for assigning the specified data in the trajectory tracking result to the target set identifier .
  • the data in the database retrieved by the server may include camera capture results, file capture results, camera alarm results, video alarm results, file alarm results, locally associated pictures, and other data.
  • the user can also track the data classified into the data set.
  • the target set ID corresponding to the target data set is given.
  • the set ID of the existing data set can be displayed for the user Select a collection ID as the target collection ID to receive the user's trajectory tracking request for the target collection ID; obtain multiple data corresponding to the target collection ID, and use the multiple data corresponding to the target collection ID as the retrieval basis to retrieve from the server
  • Other data associated with multiple data corresponding to the target set identifier to obtain the track tracking result for example, according to one or more pictures corresponding to the target set identifier, retrieve other pictures associated with one or more pictures from the server; Display the trajectory tracking results.
  • the user can judge the multiple displayed data and determine whether to add the target data set.
  • each data can be displayed with a grouping button.
  • the collection ID of the existing data collection is displayed, and the collection ID selected by the user is obtained as the target collection ID, so as to receive the data that the user assigns the designated data corresponding to the collection button to the target collection ID.
  • Into the collection request Realize the trajectory tracking of the data in the target data set, obtain more data associated with the target data set, and put it into the target data set, thereby enriching the data of the target data set, and can check the target corresponding to the target data set. The judgment of the event provides more reference.
  • the categorized button may be a clue type option (for example, it may include the same option and similar option, indicating that the user determines that the data belongs to the target data set and that the user believes that the data belongs to the target data set with a high probability but is not completely determined),
  • the user selects the type of clue when the data is included in the data set, and then selects this data.
  • the user can select multiple clue types of data to be included in the data set, and click on the display page Batch grouping into the collection button, so that the data of the lead type selected by the user is grouped into the data collection together.
  • Step 102 According to the data classification request, the data corresponding to the data identification is classified into a target data set corresponding to the target set identification, and the target data set includes a plurality of data associated with a target event.
  • the target event can be a case, such as a traffic violation case.
  • the plurality of data associated with the target event may include data of one or more people associated with the target event, and may also include data of other things associated with the target event.
  • the target data set may include data associated with the target event The data of person A, person B and car C.
  • Step 103 Receive an analysis request for the target set identifier.
  • the analysis request may include a preset dimension aggregation request or a data viewing request; the preset dimension may include at least one of target, time, location, day, hour, equipment, and latitude and longitude.
  • the target can be a target in the data, such as a person or an object in a captured image.
  • the device can be a capture device, the latitude and longitude can be the latitude and longitude where the capture device is located, and the location can also be determined according to the installation location of the capture device.
  • the data viewing request can include a data list page viewing request, a data detail page viewing request, a data export request, or a statistical report generation request, etc.
  • the user's analysis request for the target set identification can be received through the operation page.
  • Step 104 Obtain multiple data corresponding to the target set identifier, and analyze the multiple data according to the analysis method in the analysis request to obtain an analysis result.
  • the multiple data After receiving the analysis request for the target set identifier, obtain multiple data corresponding to the target set identifier from the database, that is, obtain multiple data in the target data set corresponding to the target set identifier, according to the analysis method in the analysis request
  • the multiple data is analyzed to obtain the analysis result. For example, when the analysis request is a time aggregation request, the multiple data is aggregated according to time to obtain the analysis result.
  • the analysis result can also be output to display the analysis result.
  • the analysis request is a preset dimension aggregation request
  • the display form of the analysis result can be displayed in the form of a bar chart, a pie chart, etc.
  • the analysis request is a data view request
  • the data is displayed or exported according to the data view method in the data view request.
  • the generated statistical report can display the data of different data sources corresponding to the target set identifier, so that the entire research and judgment process of the target event can be recorded .
  • the data corresponding to the data identifier is assigned to the target data set corresponding to the target set identifier, and the target data set includes the target event
  • Multiple associated data receive an analysis request for the target set identifier, obtain multiple data corresponding to the target set identifier, and analyze the multiple data according to the analysis method in the analysis request to obtain the analysis result.
  • Multiple data associated with the target event are grouped into a target data set, which solves the problem of not being able to collect the data of a target event, and can analyze the target event based on multiple data in the target data set, and realize the Analysis of target events.
  • Fig. 2 is a flow chart of the steps of a data analysis method provided by an embodiment of the present invention, which may be executed by an electronic device. As shown in Fig. 2, the method may include:
  • Step 201 Save the data added to the clue database and the data classified into the data collection through a data table, the data table including: a data identification field, a data status field, a collection identification field, a user identification field, and an update time field.
  • the data in the clue database is clue data, which means that the user considers a piece of data to be clue data and adds it to the clue database.
  • the data in the clue database is bound to the user, that is, the current user can only view the clue data corresponding to the current user ID.
  • Use another table to save the data classified into the data set which can save storage space, avoid data transmission when the data in the clue library is classified into the data set, and facilitate data management.
  • the format of the data table is shown in Table 1.
  • the data table may also include a clue type field, and the value of the clue type field is the same or similar.
  • the clue type is determined when the user adds a piece of data to the clue database, or it can also be determined when the track tracking result is included in the data set.
  • the clue type corresponding to the data in the data table can be modified by the user.
  • the data status can include included in the collection, not included in the collection, or deleted.
  • the data identifier can be a snapshot ID, an alarm ID, or a randomly generated UUID (Universally Unique Identifier).
  • the data is added to the result of the camera capture, file capture, camera alarm, video alarm, and file alarm.
  • the data identifier is a snapshot ID or an alarm ID.
  • a UUID can be randomly generated as the data identifier of the data.
  • the data is saved to the above data table.
  • the data status of the data in the data table is changed from not included in the collection to included in the collection, and the collection ID is added as the target collection ID given by the user.
  • the data enters the data table, the clue status is classified as the collection, and the collection ID is recorded as the target collection ID given by the user.
  • Each piece of data has a clue type, and the user can change the clue type corresponding to the data added to the clue database or included in the data set.
  • the user can also delete a piece of data in the clue database or in the data set, and the data status of the corresponding data in the data table is recorded as deleted. If the data in the clue database is deleted, its data status is deleted and the collection ID is empty; if the data after archiving is deleted, its data status is deleted, and the collection ID is non-empty, that is, the collection ID is before deletion. The collection ID.
  • the current user can view the data that he added to the clue database.
  • the value of the data status field is not included in the collection, the value of the collection identification field is empty, and the value of the user identification field is set
  • the user ID of the current user is used as a joint index, and the data with the joint index is filtered from the data table, and the filtered data is returned to the current user.
  • the value of the data status field is not included in the collection, the value of the collection identification field is empty, and the value of the user identification field is userid2.
  • the data is filtered from the data table and displayed to the current user. The current user can only view the data added to the lead library by the current user but cannot see the data added to the lead library by other users.
  • the current user can view the data that he has included in the data collection, or the data that other users have included in the data collection.
  • the value of the data status field is included in the collection and the collection ID
  • the value of the field is the collection identifier in the collection data view request as a joint index, and the data is filtered from the data table according to the joint index and displayed to the current user. For example, if the current user userid2 views the data classified into the data set, the value of the data status field is classified into the set, the value of the set identification field is not empty, and the value of the set identification field is the set identification specified by the user. From the data table Filter data to show to users.
  • the current user can see the data classified by other users into the data set, allowing multiple users to operate on the same data set, that is, allowing users to view or share other users' operations on the same data set, because there may be more than one target event.
  • Each user is responsible for processing.
  • whether multiple users are allowed to operate on the same data set and which users are allowed to operate on a certain data set can be set according to user needs.
  • the data of the same data identifier can be repeatedly stored as multiple data records in the data table. This is because these data may be added to the clue database by different users, that is, the corresponding user identifiers are different, or , These data may be added to the clue database by the same user, but they should be classified into different data sets, that is, the set IDs corresponding to these data are different. However, the same data added by a user to the lead library is only saved as one data record; the same data that is included in the same data set by different users is only saved as one data record.
  • Step 202 Receive a thread addition request for specified data from the current user, where the thread addition request includes the data identifier of the specified data.
  • Current users can retrieve data from the data source through keywords, and display the retrieved data on the retrieval result display page.
  • search in the data source according to the keywords in the search request to obtain the search result, and display the search result on the search result display page.
  • the current user can browse the search result displayed on the search result display page. If you think a piece of data is a clue, you can add the piece of data to the clue database.
  • the search result display page can display a clue add button corresponding to each piece of data.
  • the current user can click the clue add button corresponding to the data to be added to the clue database, so that the front end Upon receiving the thread addition request of the current user for the specified data, the front end may send the thread addition request to the electronic device, so that the electronic device receives the current user's thread addition request for the specified data.
  • the current user can also track multiple data corresponding to the target set identifier to obtain the track tracking result.
  • the current user can also receive the current user's request for adding a clue to the specified data, that is, on the track tracking result display page
  • the current user can click the clue add button corresponding to the data to be added to the clue database, so that the front end receives the current user’s request for clue addition for the specified data, and the front end can send the clue addition request to the electronic Device, so that the electronic device receives the current user's thread addition request for the specified data.
  • the clue adding button may be a clue type option (for example, it may include the same option and similar options).
  • the clue type of the specified data is selected, so that the specified data is selected, and the search Result display page or trajectory tracking result display page.
  • the current user can select multiple data to be added to the clue library through the above method, and retrieve the add clue database button on the result display page or trajectory tracking result display page, and the front end receives these multiple designations Data clue adding request, so that multiple data selected by the current user can be added to the clue database together.
  • the value of the data identification field is the data identification of the specified data
  • the value of the data status field is not included in the collection
  • the value of the collection identification field is empty
  • the value of the user identification field is the user identification of the current user.
  • the joint index is used to query whether there is a data record corresponding to the joint index from the data table.
  • the data added to the clue database needs to be data that is not included in the data set, that is, the data status is not included in the set and the set identifier is empty , And the data in the clue database is bound to the user. Different users can add a piece of the same data to the clue database. That is, a data record will be saved for each user in the data table.
  • the value of the data identification field needs to be Specify the data ID of the data, the value of the data status field is not included in the collection, the value of the collection ID field is empty, and the value of the user ID field is the user ID of the current user as the joint index, and query from the data table whether there is said
  • the data records corresponding to the joint index are then used to determine whether the specified data has been saved as clue data according to the query results.
  • Step 204 If the data record corresponding to the joint index is queried from the data table, update the update time corresponding to the joint index in the data table to the current time.
  • the data record corresponding to the joint index is queried from the data table, it means that the current user has previously added the specified data to the clue database and does not need to be added repeatedly. This time, only the update time corresponding to the joint index needs to be updated to current time.
  • Step 205 If the data record corresponding to the joint index is not queried from the data table, it is determined that the data status of the specified data is not included in the collection, the collection identifier is empty, and the update time is the current time, and the The data identification, data status, collection identification, user identification of the current user, and update time of the designated data are used as a data record and written into the data table.
  • the specified data is saved in the data table, that is, it is determined that the data status of the specified data is not included in the collection, the collection ID is empty, and the update time is current Time, the data ID, data status, collection ID, user ID of the current user, and update time of the specified data are taken as a data record, and the data record is written into the data table, thereby adding the specified data to the clue database.
  • Step 206 Receive a data classification request, where the data classification request includes a data identifier corresponding to the data to be classified into the target data set and a target collection identifier corresponding to the target data set.
  • Step 207 According to the data classification request, the data corresponding to the data identification is classified into the target data set corresponding to the target set identification, and the target data set includes a plurality of data associated with the target event.
  • the classification of the data corresponding to the data identification into the target data set corresponding to the target set identification includes: setting the value of the data identification field For the data identification, the value of the data status field is not included in the collection, the value of the collection identification field is empty, and the value of the user identification field is the user identification of the current user as the first joint index, query whether there is any
  • the data record corresponding to the first joint index is used to obtain the clue query result;
  • the value of the data identification field is the data identification, the value of the data status field is classified into the collection, and the value of the collection identification field is the target collection identification as the second A joint index, inquiring from the data table whether there is a data record corresponding to the second joint index, to obtain a set query result;
  • the clue query result and the set query result the data corresponding to the data identifier is classified into the target Under the target data set corresponding to the set identifier, and update the data status corresponding to the data identifier to be included
  • the data collection request may come from the lead data display page or the track tracking result display page, in order to avoid repeated storage of the data included in the data collection, when the data collection request is received, it is necessary to determine the data collection to be included Whether the data is in the clue database, and determine whether the data has been included in the data collection.
  • the data in the clue database needs to be data that is not included in the data set.
  • the value of the data identification field is the data identifier of the data in the collection request.
  • the value of the data status field is not included in the collection, the value of the collection ID field is empty, and the value of the user ID field is the user ID of the current user as the first joint index.
  • the data that has been included in the data set can be the data included in the data set by the current user, or the data included in the data set by other users, that is, the data included in the data set is not bound to the user, and multiple users group the same data When entering the same data collection, only one data record corresponding to the collection ID will be retained. Therefore, the value of the data ID field only needs to be included in the data ID in the collection request, and the value of the data status field is archived and The value of the collection ID field is the target collection ID as the second joint index, and the data table is queried whether there is a data record corresponding to the second joint index, and the result of the collection query is obtained.
  • the data corresponding to the data identifier in the data collection request is classified under the target data collection corresponding to the target collection ID, and the data status corresponding to the data ID is updated to be included in the collection.
  • the clue query result and the collection query result the data is classified into the data collection, which can avoid the repeated storage of the data.
  • the data corresponding to the data identifier is classified into the target data set corresponding to the target set identifier, and the data status corresponding to the data identifier is updated to be returned Into a collection, including at least one of the following: if the clue query result is empty and the collection query result is empty, add a data record corresponding to the data identifier in the data table, and mark the data in the data record The corresponding data status record is classified as a collection, the collection ID corresponding to the data ID is recorded as the target collection ID, and the update time is recorded as the current time; if the clue query result is non-empty and the collection query result is non-empty , Delete the data record corresponding to the first joint index in the data table, and update the update time corresponding to the second joint index to the current time; if the clue query result is non-empty and the set If the query result is empty, the set identifier corresponding to the data identifier is recorded as the target set identifier
  • the clue query result is empty and the set query result is empty, that is, the data to be classified into the target data set does not exist in the clue database and is not included in the set, indicating that the data is the data obtained through trajectory tracking and the result is tracked in the trajectory
  • the data received on the display page of the display page can be classified into the collection request.
  • the data can be directly classified into the target data set, that is, the data record corresponding to the data identifier to be classified into the target data set is added to the data table, and the data record ,
  • the data status is recorded as being included in the collection, the collection ID is recorded as the target collection ID, and the update time is recorded as the current time.
  • the clue query result is non-empty and the set query result is not empty, that is, the data to be classified into the target data set exists in the clue database, and the data has also been classified into the target data set before, indicating that the data has been saved in the data table
  • At least two records of the data to be archived At this time, the data record corresponding to the first joint index needs to be deleted, and the update time corresponding to the second joint index is updated to the current time.
  • Image A is directly classified into data set S.
  • the electronic device determines that image A has been added to the clue database by userid1 before, and has been included in data set S by the current user or other users, that is, image A has two pieces of data in the data table Records, one is the record that has been included in the collection, and the other is the record that the current user has added to the clue database.
  • the duplicate data needs to be deleted and the update time is updated to the current time, that is, delete and join
  • the record to the clue database, that is, the data record corresponding to the first joint index, and the update time in the record that has been included in the set, that is, the record corresponding to the second joint index is updated to the current time.
  • the clue query result is non-empty and the set query result is empty, that is, the data to be classified into the target data set exists in the clue database and is not included in the set, that is, the data has been added to the clue database by the current user but has not yet been included Collection
  • the clue data can be transferred to the set data.
  • the current user userid1 wants to directly include the image A in the data set S from the trajectory tracking result. After querying, it is determined that the image A has been added to the clue database by userid1 before, but it is not included.
  • the set identification record is S. If the result of the clue query is empty and the result of the collection query is non-empty, that is, the data to be classified into the target data set does not exist in the clue database but has been classified into the set. At this time, you only need to identify the data in the set request
  • the corresponding update time in the data table is updated to the current time. For example, the current user userid1 wants to directly include image A in the data set S from the trajectory tracking result. After querying, it is determined that image A has been included in the data set S by userid1 or other users before At this time, only the update time of the record in the table needs to be updated.
  • Step 208 Receive an analysis request for the target set identifier.
  • Step 209 Obtain multiple data corresponding to the target set identifier, and analyze the multiple data according to the analysis method in the analysis request to obtain an analysis result.
  • the data added to the clue database and the data classified into the collection are saved through the data table, which can save storage space and avoid data transmission when the data in the clue database is classified into the data collection. Change the data status in the data table and add the collection identifier, and then the data in the clue library can be classified into the data collection.
  • Fig. 3 is a structural block diagram of a data analysis device provided by an embodiment of the present invention. As shown in Fig. 3, the data analysis device may include:
  • the categorization request receiving module 301 is configured to receive a data categorization request, where the data categorization request includes a data identifier corresponding to the data to be categorized into the target data set and a target collection identifier corresponding to the target data set;
  • the data categorization module 302 is configured to categorize the data corresponding to the data identifier into the target data set corresponding to the target set identifier according to the data categorization request, and the target data set includes the data associated with the target event Multiple data;
  • the analysis request receiving module 303 is configured to receive an analysis request for the target set identifier
  • the data analysis module 304 is configured to obtain multiple data corresponding to the target set identifier, and analyze the multiple data according to the analysis method in the analysis request to obtain an analysis result.
  • the categorization request receiving module includes:
  • the thread data display unit is used to display multiple thread data corresponding to the current user on the thread data display page;
  • the first categorization request receiving unit is configured to receive the data categorization request of the current user to categorize the specified clue data into the target set identifier.
  • the categorization request receiving module includes:
  • the trajectory tracking request receiving unit is used to receive the trajectory tracking request for the target set identifier
  • a trajectory tracking unit configured to obtain a trajectory tracking result, the trajectory tracking result being other data associated with a plurality of data corresponding to the target set identifier retrieved from the server according to the trajectory tracking request;
  • a tracking result display unit for displaying the track tracking result
  • the second categorization request receiving unit is configured to receive a data categorization request for categorizing the specified data in the track tracking result under the target set identifier.
  • the device further includes:
  • the data saving module is used to save the data added to the clue database and the data classified into the data collection through a data table, the data table including: a data identification field, a data status field, a collection identification field, a user identification field and an update time field.
  • the data table further includes a thread type field, and the value of the thread type field is the same or similar.
  • the device further includes:
  • a clue addition request receiving unit configured to receive a clue addition request of a current user for specified data, where the clue addition request includes the data identifier of the specified data;
  • the first clue data query unit is used to set the value of the data identification field to the data identification of the specified data, the value of the data status field to be not included in the set, the value of the set identification field to be empty, and the value to the user identification field to be current
  • the user ID of the user is used as a joint index, and it is queried from the data table whether there is a data record corresponding to the joint index;
  • the thread data update unit is configured to update the update time corresponding to the joint index in the data table to the current time if the data record corresponding to the joint index is queried from the data table;
  • the clue data adding unit is configured to, if the data record corresponding to the joint index is not queried from the data table, determine that the data status of the specified data is not included in the collection, the collection ID is empty, and the update time is the current time, The data identification, data status, collection identification, user identification of the current user, and update time of the designated data are taken as a data record and written into the data table.
  • the data classification module includes:
  • the second clue data query unit is used to set the value of the data identification field to the data identification, the value of the data status field to be not included in the collection, the value of the collection identification field to be empty, and the value of the user identification field to be the user of the current user Identifies as the first joint index, and queries the data table for whether there is a data record corresponding to the first joint index to obtain a clue query result;
  • the collection data query unit is used to set the value of the data identification field to the data identification, the value of the data status field to be included in the set, and the value of the set identification field to use the target collection identification as the second joint index to query from the data table Whether there is a data record corresponding to the second joint index to obtain a collective query result;
  • the data categorization unit is configured to categorize the data corresponding to the data identifier into the target data set corresponding to the target set identifier according to the clue query result and the set query result, and update the data status corresponding to the data identifier Has been included in the collection.
  • the data classification unit is specifically used for:
  • the clue query result is empty and the set query result is empty, the data record corresponding to the data identifier is added to the data table, and the data status corresponding to the data identifier is recorded in the data record as returned Enter the collection, record the collection ID corresponding to the data ID as the target collection ID, and record the update time as the current time;
  • the analysis request includes a preset dimension aggregation request or a data viewing request; the preset dimension includes at least one of target, time, location, day, hour, equipment, and latitude and longitude.
  • the data analysis device receives the data classification request including the data identifier and the target set identifier through the classification request receiving module, and the data classification module classifies the data corresponding to the data identification into the target data set corresponding to the target set identifier.
  • the target data set includes multiple data associated with the target event
  • the analysis request receiving module receives an analysis request for the target set identifier
  • the data analysis module obtains multiple data corresponding to the target set identifier and follows the analysis method in the analysis request Analyze the multiple data to obtain the analysis result. Since multiple data associated with the target event can be grouped into a target data set, the problem that the data of a target event cannot be aggregated is solved, and the data of a target event can be collected according to the target. Multiple data in the data set analyzes the target event and realizes the analysis of the target event.
  • the description is relatively simple, and for related parts, please refer to the part of the description of the method embodiment.
  • the device embodiments described above are merely illustrative, where the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the objectives of the solutions of the embodiments. Those of ordinary skill in the art can understand and implement without creative work.
  • the various component embodiments of the present invention may be implemented by hardware, or by software modules running on one or more processors, or by a combination of them.
  • a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in the electronic device according to the embodiments of the present invention.
  • DSP digital signal processor
  • the present invention can also be implemented as a device or device program (for example, a computer program and a computer program product) for executing part or all of the methods described herein.
  • Such a program for realizing the present invention may be stored on a computer-readable medium, or may have the form of one or more signals.
  • Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.
  • FIG. 4 shows an electronic device that can implement the method according to the present invention.
  • the electronic device traditionally includes a processor 410 and a computer program product in the form of a memory 420 or a computer-readable medium.
  • the memory 420 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), EPROM, hard disk, or ROM.
  • the memory 420 has a storage space 430 for executing the program code 431 of any method step in the above-mentioned data analysis method.
  • the storage space 430 for program codes may include various program codes 431 respectively used to implement various steps in the above data analysis method. These program codes can be read from or written into one or more computer program products.
  • These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards, or floppy disks.
  • Such a computer program product is usually a portable or fixed storage unit as described with reference to FIG. 5.
  • the storage unit may have storage segments, storage spaces, etc., arranged similarly to the storage 420 in the electronic device of FIG. 4.
  • the program code can be compressed in a suitable form, for example.
  • the storage unit includes computer-readable codes 431', that is, codes that can be read by, for example, a processor such as 410. These codes, when run by an electronic device, cause the electronic device to execute the data analysis method described above. The various steps.
  • the embodiments of the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may adopt the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing terminal equipment to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction device.
  • the instruction device implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.
  • These computer program instructions can also be loaded on a computer or other programmable data processing terminal equipment, so that a series of operation steps are executed on the computer or other programmable terminal equipment to produce computer-implemented processing, so that the computer or other programmable terminal equipment
  • the instructions executed above provide steps for implementing functions specified in a flow or multiple flows in the flowchart and/or a block or multiple blocks in the block diagram.

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Abstract

本发明提供了一种数据分析方法、装置、电子设备及存储介质，该方法包括：接收数据归入集合请求，数据归入集合请求包括待归入目标数据集合的数据对应的数据标识和目标集合标识；将数据标识对应的数据归入目标集合标识对应的目标数据集合下，目标数据集合包括与目标事件相关联的多个数据；接收对目标集合标识的分析请求；获取目标集合标识对应的多个数据，并按照分析请求中的分析方式对所述多个数据进行分析，得到分析结果。本发明由于可以将目标事件相关联的多个数据归入一个目标数据集合中，解决了无法对一个目标事件的数据进行汇集的问题，而且可以根据目标数据集合中的多个数据对目标事件进行分析，实现了对目标事件的分析。

Description

数据分析方法、装置、电子设备及存储介质
本申请要求在2020年6月5日提交中国专利局、申请号为202010508187.1、发明名称为“数据分析方法、装置、电子设备及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及数据处理技术领域，特别是涉及一种数据分析方法、装置、电子设备及存储介质。
背景技术
现有技术中，对图像或其他信息进行管理时，只能将同一人的图像或与此人相关的其他信息放入一个集合，例如，可以把人A被拍到的多张图片归入一个集合。
但是，归属于同一集合的多个数据可能属于不同的事件，同时同一事件的数据可能会归属于不同的集合，导致无法对同一事件相关的信息进行分析。
发明内容
鉴于上述问题，提出了本发明实施例以便提供一种克服上述问题或者至少部分地解决上述问题的一种数据分析方法、装置、电子设备及存储介质。
依据本发明实施例的第一方面，提供了一种数据分析方法，包括：
接收数据归入集合请求，所述数据归入集合请求包括待归入目标数据集合的数据对应的数据标识和目标数据集合对应的目标集合标识；
根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，所述目标数据集合包括与目标事件相关联的多个数据；
接收对所述目标集合标识的分析请求；
获取所述目标集合标识对应的多个数据，并按照所述分析请求中的分析方式对所述多个数据进行分析，得到分析结果。
依据本发明实施例的第二方面，提供了一种数据分析装置，包括：
归入请求接收模块，用于接收数据归入集合请求，所述数据归入集合请求包括待归入目标数据集合的数据对应的数据标识和目标数据集合对应的目标集合标识；
数据归入模块，用于根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，所述目标数据集合包括与目标事件相关联的多个数据；
分析请求接收模块，用于接收对所述目标集合标识的分析请求；
数据分析模块，用于获取所述目标集合标识对应的多个数据，并按照所述分析请求中的分析方式对所述多个数据进行分析，得到分析结果。
依据本发明实施例的第三方面，提供了一种电子设备，包括：
存储器，其中存储有计算机可读代码；
一个或多个处理器，当所述计算机可读代码被所述一个或多个处理器执行时，所述计算处理设备执行如第一方面中所述的数据分析方法。
依据本发明实施例的第四方面，提供了一种计算机程序，包括计算机可读代码，当所述计算机可读代码在计算处理设备上运行时，导致所述计算处理设备执行如第一方面所述的数据分析方法。
根据本发明实施例的第五方面，提供了一种计算机可读介质，其中存储了如第四方面所述的计算机程序。
本发明实施例提供的数据分析方法、装置、电子设备及存储介质，通过接收包括数据标识和目标集合标识的数据归入集合请求，将数据标识对应的数据归入目标集合标识对应的目标数据集合下，目标数据集合包括与目标事件相关联的多个数据，接收对目标集合标识的分析请求，获取目标集合标识对应的多个数据，并按照分析请求中的分析方式对所述多个数据进行分析，得到分析结果，由于可以将目标事件相关联的多个数据归入一个目标数据集合中，解决了无法对一个目标事件的数据进行汇集的问题，而且可以根据目标数据集合中的多个数据对目标事件进行分析，实现了对目标事件的多维度分析。
上述说明仅是本发明技术方案的概述，为了能够更清楚了解本发明的技术手段，而可依照说明书的内容予以实施，并且为了让本发明的上述和其它目的、特征和优点能够更明显易懂，以下特举本发明的具体实施方式。
附图说明
通过阅读下文优选实施方式的详细描述，各种其他的优点和益处对于本领域普通技术人员将变得清楚明了。附图仅用于示出优选实施方式的目的，而并不认为是对本发明的限制。
图1是本发明实施例提供的一种数据分析方法的步骤流程图；
图2是本发明实施例提供的一种数据分析方法的步骤流程图；
图3是本发明实施例提供的一种数据分析装置的结构框图；
图4示意性地示出了用于执行根据本发明的方法的电子设备的框图；以及
图5示意性地示出了用于保持或者携带实现根据本发明的方法的程序代码的存储单元。
具体实施例
下面将参照附图更详细地描述本发明的示例性实施例。虽然附图中显示了本发明的示例性实施例，然而应当理解，可以以各种形式实现本发明而不应被这里阐述的实施例所限制。相反，提供这些实施例是为了能够更透彻地理解本发明，并且能够将本发明的范围完整的传达给本领域的技术人员。
图1是本发明实施例提供的一种数据分析方法的步骤流程图，可以由电子设备执行，如图1所示，该方法可以包括：
步骤101，接收数据归入集合请求，所述数据归入集合请求包括待归入目标数据集合的数据对应的数据标识和目标数据集合对应的目标集合标识。
数据归入集合请求由当前用户从线索数据显示页面发出或者从轨迹追踪结果的显示页面发出。其中，线索数据显示页面显示当前用户加入线索库的线索数据。轨迹追踪是根据当前用户对目标集合标识的轨迹追踪请求从服务器获取到的数据源中检索与目标集合标识对应的多个数据相关联的数据的过程。可以理解的是，与目标集合标识对应的多个数据可以是图片数据，检索与目标集合标识对应的多个数据相关联的数据可以是根据图片数据检索与该图片数据相似度高于阈值、时空关系满足预设条件的图片数据。
在本发明的一个实施例中，所述接收数据归入集合请求包括：在线索 数据显示页面，显示当前用户对应的多个线索数据；接收当前用户将指定线索数据归入目标集合标识下的数据归入集合请求。
其中，当前用户对应的多个线索数据是当前用户加入线索库的数据。所述线索数据包括相机抓拍结果、文件抓拍结果、相机告警结果、录像告警结果、文件告警结果和本地关联图片中的至少一种。本地关联图片可以是用户终端中保存的图片。
在接收到线索数据查看请求时，从线索库中获取当前用户对应的线索数据，并在线索数据显示页面显示当前用户对应的多个线索数据，对应每个线索数据可以显示归入集合按钮，通过归入集合按钮接收当前用户的数据归入集合请求，若检测到当前用户对指定线索数据的归入集合按钮的点击操作，则显示已有数据集合的数据集合标识，并获取用户选择的数据集合标识，作为目标集合标识，从而接收到当前用户将指定线索数据归入目标集合标识下的数据归入集合请求。通过显示数据显示页面实现了将加入线索库的数据归入目标数据集合中。其中，数据集合标识可以包括数据集合名称和/或数据集合ID。
在本发明的另一个实施例中，所述接收数据归入集合请求包括：接收对目标集合标识的轨迹追踪请求；获取轨迹追踪结果，所述轨迹追踪结果是根据所述轨迹追踪请求，从服务器中检索的与所述目标集合标识对应的多个数据相关联的其他数据；显示所述轨迹追踪结果；接收将轨迹追踪结果中的指定数据归入所述目标集合标识下的数据归入集合请求。
其中，服务器检索的数据库中的数据可以包括相机抓拍结果、文件抓拍结果、相机告警结果、录像告警结果、文件告警结果、本地关联图片和其他数据。
用户还可以对归入数据集合的数据进行轨迹追踪，在需要对一个目标数据集合进行轨迹追踪时，给出该目标数据集合对应的目标集合标识，例如可以显示已有数据集合的集合标识供用户选择一个集合标识作为目标集合标识，从而接收到用户对目标集合标识的轨迹追踪请求；获取目标集合标识对应的多个数据，并将目标集合标识对应的多个数据作为检索依据，从服务器中检索与目标集合标识对应的多个数据相关联的其他数据，得到轨迹追踪结果，例如，根据目标集合标识对应的一个或多个图片，将服务 器中检索与一个或多个图片相关联的其他图片；显示轨迹追踪结果，用户可以对显示的多个数据进行判断，确定是否加入目标数据集合，在轨迹追踪结果的显示页面对应每个数据可以显示归入集合按钮，在检测到用户对该归入集合按钮的点击操作时，显示已有数据集合的集合标识，并获取用户选择的集合标识，作为目标集合标识，从而接收到用户将归入集合按钮对应的指定数据归入目标集合标识下的数据归入集合请求。实现了对目标数据集合中的数据进行轨迹追踪，获取与目标数据集合相关联的更多数据，并归入目标数据集合中，从而丰富了目标数据集合的数据，可以对目标数据集合对应的目标事件的判断提供更多的参考。
其中，所述归入集合按钮可以是线索类型选项(如可以包括相同选项和相似选项，分别表明用户确定该数据属于目标数据集合和用户认为该数据大概率属于目标数据集合但不完全确定)，用户选择将数据归入数据集合时的线索类型，从而选中这条数据，在轨迹追踪结果的显示页面，用户可以选中多个要归入数据集合的数据的线索类型，并点击该显示页面中的批量归入集合的按钮，从而将用户选中线索类型的数据一起归入数据集合。
步骤102，根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，所述目标数据集合包括与目标事件相关联的多个数据。
在接收到数据归入集合请求后，建立待归入目标数据集合的数据对应的数据标识和目标集合标识的对应关系，并对应保存所述对应关系和所述数据。其中，目标事件可以是一个案件，例如交通违法案件等。与目标事件相关联的多个数据可以包括与目标事件相关联的一个或多个人的数据，还可以包括与目标事件相关联的其他事物的数据，例如，目标数据集合可以包括与目标事件相关联的人A、人B和车C的数据。
步骤103，接收对所述目标集合标识的分析请求。
其中，所述分析请求可以包括预设维度聚合请求或数据查看请求；预设维度可以包括目标、时间、地点、天、小时、设备和经纬度中的至少一种。目标可以是数据中的目标，如一张抓拍图像中的人或物等。设备可以是抓拍设备，经纬度可以是抓拍设备所在的经纬度，地点也可以根据抓拍设备的安装地点确定。数据查看请求可以包括数据列表页查看请求、数据 详情页查看请求、数据导出请求或统计报表生成请求等。
可以通过操作页面接收用户对目标集合标识的分析请求。
步骤104，获取所述目标集合标识对应的多个数据，并按照所述分析请求中的分析方式对所述多个数据进行分析，得到分析结果。
在接收到对目标集合标识的分析请求后，从数据库中获取所述目标集合标识对应的多个数据，即获取目标集合标识对应的目标数据集合中的多个数据，按照分析请求中的分析方式对所述多个数据进行分析，得到分析结果，例如所述分析请求为按时间聚合请求时，则按照时间对多个数据进行聚合，得到分析结果。
在得到分析结果后，还可以输出所述分析结果，以对分析结果进行展示。在分析请求为预设维度聚合请求时，分析结果的展示形式可以展示为柱状图、饼形图等形式。在分析请求为数据查看请求时，按照数据查看请求中的数据查看方式展示或导出数据，如生成的统计报表可以展示目标集合标识对应的不同数据源的数据，从而可以记录目标事件的整个研判过程。
本实施例提供的数据分析方法，通过接收包括数据标识和目标集合标识的数据归入集合请求，将数据标识对应的数据归入目标集合标识对应的目标数据集合下，目标数据集合包括与目标事件相关联的多个数据，接收对目标集合标识的分析请求，获取目标集合标识对应的多个数据，并按照分析请求中的分析方式对所述多个数据进行分析，得到分析结果，由于可以将目标事件相关联的多个数据归入一个目标数据集合中，解决了无法对一个目标事件的数据进行汇集的问题，而且可以根据目标数据集合中的多个数据对目标事件进行分析，实现了对目标事件的分析。
图2是本发明实施例提供的一种数据分析方法的步骤流程图，可以由电子设备执行，如图2所示，该方法可以包括：
步骤201，通过数据表保存加入线索库的数据和归入数据集合的数据，所述数据表包括：数据标识字段、数据状态字段、集合标识字段、用户标识字段和更新时间字段。
其中，线索库中的数据是线索数据，是用户认为一条数据是线索数据从而加入线索库中，线索库中的数据与用户绑定，即当前用户只能查看当 前用户标识对应的线索数据。
通过一张数据表来保存加入线索库的数据和归入数据集合的数据，并通过数据表的字段来区分线索库中的数据和归入数据集合的数据，而不用单独使用一张表保存线索数据并使用另一张表保存归入数据集合的数据，从而可以节省存储空间，并避免了将线索库中的数据归入数据集合时的数据传输，同时便于数据管理。
所述数据表的格式如表1所示，所述数据表还可以包括线索类型字段，所述线索类型字段的值为相同或相似。线索类型是用户将一条数据加入线索库时确定的，或者，也可以是将轨迹追踪结果归入数据集合时确定的，当然，在数据表中的数据对应的线索类型可以由用户进行修改。数据状态可以包括已归入集合、未归入集合或已删除等。数据标识可以是抓拍ID、告警ID或者随机生成的UUID(Universally Unique Identifier，通用唯一识别码)，在数据是由相机抓拍结果、文件抓拍结果、相机告警结果、录像告警结果、文件告警结果加入到数据表中时，数据标识是抓拍ID或告警ID，在数据是由本地关联图片加入到数据表中时，可以随机生成一个UUID作为该数据的数据标识。
表1数据表
Figure PCTCN2020118406-appb-000001
用户将一条数据添加到线索库时，将数据保存到上述数据表。用户将已在线索库的数据归入数据集合时，在数据表中将该数据的数据状态由未归入集合改为已归入集合，并添加集合标识为用户给出的目标集合标识。用户确认某条轨迹追踪结果数据归入数据集合时，该数据进入数据表，线索状态为已归入集合，并将集合标识记录为用户给出的目标集合标识。每条数据都有线索类型，用户可以更改添加到线索库或归入数据集合的数据 对应的线索类型。用户还可以删除线索库或归入数据集合中的某条数据，则对应数据在数据表中的数据状态记录为已删除。如果线索库中的数据被删除，则其数据状态为已删除，集合标识为空；如果归档后的数据被删除，则其数据状态为已删除，集合标识为非空，即集合标识为删除前的集合标识。
当前用户可以查看自己添加到线索库中的数据，在接收到当前用户的线索数据查看请求时，将数据状态字段的值为未归入集合、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为联合索引，并从数据表中筛选具有该联合索引的数据，并将筛选到的数据返回给当前用户。例如，当前用户userid2查看线索库中的数据，则使用数据状态字段的值为未归入集合、集合标识字段的值为空、用户标识字段的值为userid2从数据表中筛选数据展示给该当前用户。当前用户只能查看当前用户添加到线索库中的数据而不能看到其他用户添加到线索库中的数据。
当前用户可以查看自己归入数据集合的数据，也可以查看其他用户归入数据集合的数据，在接收到当前用户的集合数据查看请求时，将数据状态字段的值为已归入集合和集合标识字段的值为集合数据查看请求中的集合标识作为联合索引，根据该联合索引从数据表中筛选数据并展示给当前用户。例如，当前用户userid2查看归入数据集合的数据，则将数据状态字段的值为已归入集合、集合标识字段的值不为空且集合标识字段的值为用户指定的集合标识从数据表中筛选数据展示给用户。当前用户可以看到其他用户归入数据集合的数据，允许多个用户对同一数据集合进行操作，也就是允许用户查看或共享其他用户对同一数据集合的操作，因为对于一个目标事件有可能有多个用户负责处理。当然，是否允许多个用户对同一数据集合进行操作、允许哪些用户对某一数据集合进行操作可以根据用户需求设置。
需要说明的是，同一个数据标识的数据，可以在数据表中重复存储为多条数据记录，这是因为，这些数据可能由不同用户添加到线索库，即对应的用户标识是不同的，或者，这些数据可能由同一用户添加到线索库但要归入不同数据集合，即这些数据对应的集合标识是不同的。但是，一个用户添加到线索库的同一数据，只保存为一条数据记录；不同用户归入同 一数据集合的同一数据，只保存为一条数据记录。
步骤202，接收当前用户对指定数据的线索添加请求，所述线索添加请求包括所述指定数据的数据标识。
当前用户可以通过关键词来检索数据源中的数据，并在检索结果展示页面展示检索到的数据。在接收到当前用户的检索请求时，根据检索请求中的关键词在数据源中检索，得到检索结果，并在检索结果展示页面展示检索结果，当前用户可以浏览检索结果展示页面展示的检索结果，若认为一条数据是线索，可以将该条数据加入线索库，检索结果展示页面中可以对应每条数据显示线索添加按钮，当前用户可以点击要添加到线索库的数据对应的线索添加按钮，从而前端接收到当前用户对该指定数据的线索添加请求，前端可以将线索添加请求发送至电子设备，从而电子设备接收到当前用户对指定数据的线索添加请求。
当前用户还可以通过对目标集合标识对应的多个数据进行轨迹追踪，得到轨迹追踪结果，在轨迹追踪结果展示页面，也可以接收当前用户对指定数据的线索添加请求，即在轨迹追踪结果展示页面对应每条数据显示线索添加按钮，当前用户可以点击要添加到线索库的数据对应的线索添加按钮，从而前端接收到当前用户对该指定数据的线索添加请求，前端可以将线索添加请求发送至电子设备，从而电子设备接收到当前用户对指定数据的线索添加请求。
所述线索添加按钮可以是线索类型选项(如可以包括相同选项和相似选项)的按钮，当前用户选中要添加的指定数据时，选中该指定数据的线索类型，从而将该指定数据选中，在检索结果展示页面或轨迹追踪结果展示页面当前用户可以通过上述方式选中想要加入线索库的多个数据，并检索结果展示页面或轨迹追踪结果展示页面的加入线索库按钮，前端接收到这多个指定数据的线索添加请求，从而可以将当前用户选中的多个数据一起加入线索库。
步骤203，将所述数据标识字段的值为指定数据的数据标识、数据状态字段的值为未归归入集合、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为联合索引，从所述数据表中查询是否有所述联合索引对应的数据记录。
在接收到当前用户的线索添加请求时，避免保存当前用户加入重复数据，可以在将指定数据加入线索库时确定该指定数据是否已在数据表中保存，如果已保存，则需要对更新时间进行更新，如果未保存，则将指定数据保存到数据表中并指明是加入线索库的数据。
在确定指定数据是否已在数据表中保存时，通过数据表中的字段的值来确定。由于加入线索库的数据和归入数据集合的数据保存在一张数据表中，因此加入线索库的数据需要是未归入数据集合的数据，即数据状态为未归入集合、集合标识为空，而且线索库中的数据与用户绑定，不同的用户可以分别将一条相同数据加入线索库，即在数据表中会对应每个用户保存一条数据记录，因此，需要将数据标识字段的值为指定数据的数据标识、数据状态字段的值为未归入集合、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为联合索引，并从数据表中查询是否有所述联合索引对应的数据记录，进而根据查询结果确定指定数据是否已保存为线索数据。
步骤204，若从数据表中查询到所述联合索引对应的数据记录，则将数据表中所述联合索引对应的更新时间更新为当前时间。
若从数据表中查询到所述联合索引对应的数据记录，则说明当前用户之前已将指定数据添加到线索库，不需要重复添加，本次只需要将所述联合索引对应的更新时间更新为当前时间。
步骤205，若从数据表中未查询到所述联合索引对应的数据记录，则确定所述指定数据的数据状态为未归入集合、集合标识为空、更新时间为当前时间，并将所述指定数据的数据标识、数据状态、集合标识、当前用户的用户标识和更新时间作为一条数据记录，并写入到所述数据表中。
若从数据表中未查询到所述联合索引对应的数据记录，则将该指定数据保存到数据表中，即确定指定数据的数据状态为未归入集合、集合标识为空、更新时间为当前时间，将指定数据的数据标识、数据状态、集合标识、当前用户的用户标识和更新时间作为一条数据记录，并将该数据记录写入到数据表中，从而将指定数据添加至线索库。
步骤206，接收数据归入集合请求，所述数据归入集合请求包括待归入目标数据集合的数据对应的数据标识和目标数据集合对应的目标集合标 识。
步骤207，根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，所述目标数据集合包括与目标事件相关联的多个数据。
在本发明的一个实施例中，所述根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，包括：将数据标识字段的值为所述数据标识、数据状态字段的值为未归入集合、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为第一联合索引，从数据表中查询是否有所述第一联合索引对应的数据记录，得到线索查询结果；将数据标识字段的值为所述数据标识、数据状态字段的值为已归入集合和集合标识字段的值为目标集合标识作为第二联合索引，从数据表中查询是否有所述第二联合索引对应的数据记录，得到集合查询结果；根据所述线索查询结果和集合查询结果，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，并更新所述数据标识对应的数据状态为已归入集合。
由于数据归入集合请求可能来自于线索数据展示页面或者轨迹追踪结果展示页面，为了避免对归入数据集合的数据进行重复存储，在接收到数据归入集合请求时，需要确定待归入数据集合的数据是否在线索库中，并确定该数据是否已归入数据集合。在线索库中的数据需要是未归入数据集合的数据，在确定待归入数据集合的数据是否在线索库中时，通过将数据标识字段的值为数据归入集合请求中的数据标识、数据状态字段的值为未归入集合、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为第一联合索引，从数据表中查询是否有第一联合索引对应的数据记录，得到线索查询结果。已归入数据集合的数据可以是当前用户归入数据集合的数据，也可以是其他用户归入数据集合的数据，即归入数据集合的数据不与用户绑定，多个用户将同一数据归入同一数据集合时，只会保留该数据对应该集合标识的一条数据记录，因此，只需将数据标识字段的值为数据归入集合请求中的数据标识、数据状态字段的值为已归档和集合标识字段的值为目标集合标识作为第二联合索引，并在数据表中查询是否有第二联合索引对应的数据记录，得到集合查询结果。根据线索查询结果 和集合查询结果，将数据归入集合请求中的数据标识对应的数据归入目标集合标识对应的目标数据集合下，并将该数据标识对应的数据状态更新为已归入集合。根据线索查询结果和集合查询结果来将数据归入数据集合，可以避免对数据的重复存储。
其中，所述根据所述线索查询结果和集合查询结果，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，并更新所述数据标识对应的数据状态为已归入集合，包括以下至少一个：若所述线索查询结果为空且所述集合查询结果为空，则在数据表中增加所述数据标识对应的数据记录，并在数据记录中将所述数据标识对应的数据状态记录为已归入集合，将数据标识对应的集合标识记录为目标集合标识，将更新时间记录为当前时间；若所述线索查询结果为非空且所述集合查询结果为非空，则在所述数据表中将所述第一联合索引对应的数据记录删除，将所述第二联合索引对应的更新时间更新为当前时间；若所述线索查询结果为非空且所述集合查询结果为空，则在所述数据表中，将所述数据标识对应的集合标识记录为目标集合标识，并将所述数据标识对应的更新时间更新为当前时间；若所述线索查询结果为空且所述集合查询结果为非空，在所述数据表中将所述数据标识对应的更新时间更新为当前时间。
若线索查询结果为空且集合查询结果为空，即待归入目标数据集合的数据在线索库中不存在而且也未归入集合，说明该数据是通过轨迹追踪得到的数据并在轨迹追踪结果的展示页面接收到的数据归入集合请求，这时可以直接将该数据归入目标数据集合，即在数据表中增加待归入目标数据集合的数据标识对应的数据记录，并在该数据记录中，将数据状态记录为已归入集合，将集合标识记录为目标集合标识，将更新时间记录为当前时间。若线索查询结果为非空且集合查询结果为非空，即待归入目标数据集合的数据在线索库中存在，同时该数据之前也已归入目标数据集合，说明数据表中已经保存了该待归档数据的至少两条记录，这时，需要删除第一联合索引对应的数据记录，同时将第二联合索引对应的更新时间更新为当前时间，例如，当前用户userid1欲从轨迹追踪结果中把图像A直接归入数据集合S，电子设备经过查询确定图像A之前已经被userid1添加到线索库，且已被当前用户或其他用户归入数据集合S，即在数据表中图像A有两 条数据记录，一条是已归入集合的记录，一条是当前用户加入到线索库的记录，在将该图像A归入数据集合S时，需删除重复数据并将更新时间更新为当前时间，即删除加入到线索库的记录，即第一联合索引对应的数据记录，并将已归入集合的记录即第二联合索引对应的记录中的更新时间更新为当前时间。若线索查询结果为非空且集合查询结果为空，即待归入目标数据集合的数据在线索库中存在而且未归入集合，即该数据已被当前用户添加到线索库，还未归入集合，这时只需在数据表中将数据归入集合请求中的数据标识对应的集合标识记录为目标集合标识，并将数据标识对应的更新时间更新为当前时间，即直接在数据表中将线索数据转移为归入集合数据即可，例如，当前用户userid1欲从轨迹追踪结果中把图像A直接归入数据集合S，经过查询确定图像A之前已经被userid1加到线索库，但未归入集合，此时只需把该条记录中的数据状态改为已归入集合，集合标识记录为S。若线索查询结果为空且集合查询结果为非空，即待归入目标数据集合的数据在线索库中不存在但是已归入集合，这时只需要将数据归入集合请求中的数据标识在数据表中对应的更新时间更新为当前时间，例如，当前用户userid1欲从轨迹追踪结果中把图像A直接归入数据集合S，经过查询确定图像A之前已经被userid1或其他用户归入数据集合S，此时只需更新表中该条记录的更新时间。通过上述处理，将归入同一数据集合的同一数据只保存一条数据记录，避免了对数据的重复存储，而且实现了多个用户共享数据集合的修改，但是当前用户只能查看自己加入线索库的数据不能查看其它用户加入线索库的数据。
步骤208，接收对所述目标集合标识的分析请求。
步骤209，获取所述目标集合标识对应的多个数据，并按照所述分析请求中的分析方式对所述多个数据进行分析，得到分析结果。
本实施例提供的数据分析方法，通过数据表保存加入线索库的数据和归入集合的数据，可以节省存储空间，并可以避免将线索库中的数据归入数据集合时的数据传输，只需在数据表中更改数据状态并添加集合标识，即可实现将线索库中的数据归入数据集合。
需要说明的是，对于方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明实施例并不受所 描述的动作顺序的限制，因为依据本发明实施例，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作并不一定是本发明实施例所必须的。
图3是本发明实施例提供的一种数据分析装置的结构框图，如3所示，该数据分析装置可以包括：
归入请求接收模块301，用于接收数据归入集合请求，所述数据归入集合请求包括待归入目标数据集合的数据对应的数据标识和目标数据集合对应的目标集合标识；
数据归入模块302，用于根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，所述目标数据集合包括与目标事件相关联的多个数据；
分析请求接收模块303，用于接收对所述目标集合标识的分析请求；
数据分析模块304，用于获取所述目标集合标识对应的多个数据，并按照所述分析请求中的分析方式对所述多个数据进行分析，得到分析结果。
可选的，所述归入请求接收模块包括：
线索数据显示单元，用于在线索数据显示页面，显示当前用户对应的多个线索数据；
第一归入请求接收单元，用于接收当前用户将指定线索数据归入目标集合标识下的数据归入集合请求。
可选的，所述归入请求接收模块包括：
轨迹追踪请求接收单元，用于接收对目标集合标识的轨迹追踪请求；
轨迹追踪单元，用于获取轨迹追踪结果，所述轨迹追踪结果是根据所述轨迹追踪请求，从服务器中检索的与所述目标集合标识对应的多个数据相关联的其他数据；
追踪结果显示单元，用于显示所述轨迹追踪结果；
第二归入请求接收单元，用于接收将轨迹追踪结果中的指定数据归入所述目标集合标识下的数据归入集合请求。
可选的，所述装置还包括：
数据保存模块，用于通过数据表保存加入线索库的数据和归入数据集 合的数据，所述数据表包括：数据标识字段、数据状态字段、集合标识字段、用户标识字段和更新时间字段。
可选的，所述数据表还包括线索类型字段，所述线索类型字段的值为相同或相似。
可选的，所述装置还包括：
线索添加请求接收单元，用于接收当前用户对指定数据的线索添加请求，所述线索添加请求包括所述指定数据的数据标识；
第一线索数据查询单元，用于将所述数据标识字段的值为指定数据的数据标识、数据状态字段的值为未归入集、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为联合索引，从所述数据表中查询是否有所述联合索引对应的数据记录；
线索数据更新单元，用于若从数据表中查询到所述联合索引对应的数据记录，则将数据表中所述联合索引对应的更新时间更新为当前时间；
线索数据添加单元，用于若从数据表中未查询到所述联合索引对应的数据记录，则确定所述指定数据的数据状态为未归入集合、集合标识为空、更新时间为当前时间，并将所述指定数据的数据标识、数据状态、集合标识、当前用户的用户标识和更新时间作为一条数据记录，并写入到所述数据表中。
可选的，所述数据归入模块包括：
第二线索数据查询单元，用于将数据标识字段的值为所述数据标识、数据状态字段的值为未归入集合、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为第一联合索引，从数据表中查询是否有所述第一联合索引对应的数据记录，得到线索查询结果；
集合数据查询单元，用于将数据标识字段的值为所述数据标识、数据状态字段的值为已归入集和集合标识字段的值为目标集合标识作为第二联合索引，从数据表中查询是否有所述第二联合索引对应的数据记录，得到集合查询结果；
数据归入单元，用于根据所述线索查询结果和集合查询结果，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，并更新所述数据标识对应的数据状态为已归入集合。
可选的，所述数据归入单元具体用于：
若所述线索查询结果为空且所述集合查询结果为空，则在数据表中增加所述数据标识对应的数据记录，并在数据记录中将所述数据标识对应的数据状态记录为已归入集合，将数据标识对应的集合标识记录为目标集合标识，将更新时间记录为当前时间；
若所述线索查询结果为非空且所述集合查询结果为非空，则在所述数据表中将所述第一联合索引对应的数据记录删除，将所述第二联合索引对应的更新时间更新为当前时间；
若所述线索查询结果为非空且所述集合查询结果为空，则在所述数据表中，将所述数据标识对应的集合标识记录为目标集合标识，并将所述数据标识对应的更新时间更新为当前时间；
若所述线索查询结果为空且所述集合查询结果为非空，在所述数据表中将所述数据标识对应的更新时间更新为当前时间。
可选的，所述分析请求包括预设维度聚合请求或数据查看请求；预设维度包括目标、时间、地点、天、小时、设备和经纬度中的至少一种。
本实施例提供的数据分析装置，通过归入请求接收模块接收包括数据标识和目标集合标识的数据归入集合请求，数据归入模块将数据标识对应的数据归入目标集合标识对应的目标数据集合下，目标数据集合包括与目标事件相关联的多个数据，分析请求接收模块接收对目标集合标识的分析请求，数据分析模块获取目标集合标识对应的多个数据，并按照分析请求中的分析方式对所述多个数据进行分析，得到分析结果，由于可以将目标事件相关联的多个数据归入一个目标数据集合中，解决了无法对一个目标事件的数据进行汇集的问题，而且可以根据目标数据集合中的多个数据对目标事件进行分析，实现了对目标事件的分析。
对于装置实施例而言，由于其与方法实施例基本相似，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现 本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。
本发明的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本发明实施例的电子设备中的一些或者全部部件的一些或者全部功能。本发明还可以实现为用于执行这里所描述的方法的一部分或者全部的设备或者装置程序(例如，计算机程序和计算机程序产品)。这样的实现本发明的程序可以存储在计算机可读介质上，或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。
例如，图4示出了可以实现根据本发明的方法的电子设备。该电子设备传统上包括处理器410和以存储器420形式的计算机程序产品或者计算机可读介质。存储器420可以是诸如闪存、EEPROM(电可擦除可编程只读存储器)、EPROM、硬盘或者ROM之类的电子存储器。存储器420具有用于执行上述数据分析方法中的任何方法步骤的程序代码431的存储空间430。例如，用于程序代码的存储空间430可以包括分别用于实现上面的数据分析方法中的各种步骤的各个程序代码431。这些程序代码可以从一个或者多个计算机程序产品中读出或者写入到这一个或者多个计算机程序产品中。这些计算机程序产品包括诸如硬盘，紧致盘(CD)、存储卡或者软盘之类的程序代码载体。这样的计算机程序产品通常为如参考图5所述的便携式或者固定存储单元。该存储单元可以具有与图4的电子设备中的存储器420类似布置的存储段、存储空间等。程序代码可以例如以适当形式进行压缩。通常，存储单元包括计算机可读代码431’，即可以由例如诸如410之类的处理器读取的代码，这些代码当由电子设备运行时，导致该电子设备执行上面所描述的数据分析方法中的各个步骤。
本说明书中的各个实施例均采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似的部分互相参见即可。
本领域内的技术人员应明白，本发明实施例的实施例可提供为方法、装置、或计算机程序产品。因此，本发明实施例可采用完全硬件实施例、 完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明实施例是参照根据本发明实施例的方法、终端设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理终端设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理终端设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理终端设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理终端设备上，使得在计算机或其他可编程终端设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程终端设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本发明实施例的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例做出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明实施例范围的所有变更和修改。
最后，还需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者终端设备不仅包括那些要 素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者终端设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者终端设备中还存在另外的相同要素。
以上对本发明所提供的一种数据分析方法、装置、电子设备及存储介质，进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (13)

  1. 一种数据分析方法，其特征在于，包括：
    接收数据归入集合请求，所述数据归入集合请求包括待归入目标数据集合的数据对应的数据标识和目标数据集合对应的目标集合标识；
    根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，所述目标数据集合包括与目标事件相关联的多个数据；
    接收对所述目标集合标识的分析请求；
    获取所述目标集合标识对应的多个数据，并按照所述分析请求中的分析方式对所述多个数据进行分析，得到分析结果。
  2. 根据权利要求1所述的方法，其特征在于，所述接收数据归入集合请求包括：
    在线索数据显示页面，显示当前用户对应的多个线索数据；
    接收当前用户将指定线索数据归入目标集合标识下的数据归入集合请求。
  3. 根据权利要求1所述的方法，其特征在于，所述接收数据归入集合请求包括：
    接收对目标集合标识的轨迹追踪请求；
    获取轨迹追踪结果，所述轨迹追踪结果是根据所述轨迹追踪请求，从服务器中检索的与所述目标集合标识对应的多个数据相关联的其他数据；
    显示所述轨迹追踪结果；
    接收将轨迹追踪结果中的指定数据归入所述目标集合标识下的数据归入集合请求。
  4. 根据权利要求1-3任一项所述的方法，其特征在于，还包括：
    通过数据表保存加入线索库的数据和归入数据集合的数据，所述数据表包括：数据标识字段、数据状态字段、集合标识字段、用户标识字段和更新时间字段。
  5. 根据权利要求4所述的方法，其特征在于，所述数据表还包括线索类型字段，所述线索类型字段的值为相同或相似。
  6. 根据权利要求4所述的方法，其特征在于，还包括：
    接收当前用户对指定数据的线索添加请求，所述线索添加请求包括所述指定数据的数据标识；
    将所述数据标识字段的值为指定数据的数据标识、数据状态字段的值为未归入集合、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为联合索引，从所述数据表中查询是否有所述联合索引对应的数据记录；
    若从数据表中查询到所述联合索引对应的数据记录，则将数据表中所述联合索引对应的更新时间更新为当前时间；
    若从数据表中未查询到所述联合索引对应的数据记录，则确定所述指定数据的数据状态为未归入集合、集合标识为空、更新时间为当前时间，并将所述指定数据的数据标识、数据状态、集合标识、当前用户的用户标识和更新时间作为一条数据记录，并写入到所述数据表中。
  7. 根据权利要求4所述的方法，其特征在于，所述根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，包括：
    将数据标识字段的值为所述数据标识、数据状态字段的值为未归入集合、集合标识字段的值为空和用户标识字段的值为当前用户的用户标识作为第一联合索引，从数据表中查询是否有所述第一联合索引对应的数据记录，得到线索查询结果；
    将数据标识字段的值为所述数据标识、数据状态字段的值为已归入集合和集合标识字段的值为目标集合标识作为第二联合索引，从数据表中查询是否有所述第二联合索引对应的数据记录，得到集合查询结果；
    根据所述线索查询结果和集合查询结果，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，并更新所述数据标识对应的数据状态为已归入集合。
  8. 根据权利要求7所述的方法，其特征在于，所述根据所述线索查询结果和集合查询结果，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，并更新所述数据标识对应的数据状态为已归入集合，包括以下至少一个：
    若所述线索查询结果为空且所述集合查询结果为空，则在数据表中增加所述数据标识对应的数据记录，并在数据记录中将所述数据标识对应的数据状态记录为已归入集合，将数据标识对应的集合标识记录为目标集合标识，将更新时间记录为当前时间；
    若所述线索查询结果为非空且所述集合查询结果为非空，则在所述数据表中将所述第一联合索引对应的数据记录删除，将所述第二联合索引对应的更新时间更新为当前时间；
    若所述线索查询结果为非空且所述集合查询结果为空，则在所述数据表中，将所述数据标识对应的集合标识记录为目标集合标识，并将所述数据标识对应的更新时间更新为当前时间；
    若所述线索查询结果为空且所述集合查询结果为非空，则在所述数据表中将所述数据标识对应的更新时间更新为当前时间。
  9. 根据权利要求1-3任一项所述的方法，其特征在于，所述分析请求包括预设维度聚合请求或数据查看请求；预设维度包括目标、时间、地点、天、小时、设备和经纬度中的至少一种。
  10. 一种数据分析装置，其特征在于，包括：
    归入请求接收模块，用于接收数据归入集合请求，所述数据归入集合请求包括待归入目标数据集合的数据对应的数据标识和目标数据集合对应的目标集合标识；
    数据归入模块，用于根据所述数据归入集合请求，将所述数据标识对应的数据归入所述目标集合标识对应的目标数据集合下，所述目标数据集合包括与目标事件相关联的多个数据；
    分析请求接收模块，用于接收对所述目标集合标识的分析请求；
    数据分析模块，用于获取所述目标集合标识对应的多个数据，并按照所述分析请求中的分析方式对所述多个数据进行分析，得到分析结果。
  11. 一种电子设备，其特征在于，包括：
    存储器，其中存储有计算机可读代码；
    一个或多个处理器，当所述计算机可读代码被所述一个或多个处理器执行时，所述计算处理设备执行如权利要求1-9任一项所述的数据分析方法。
  12. 一种计算机程序，包括计算机可读代码，当所述计算机可读代码在 计算处理设备上运行时，导致所述计算处理设备执行根据权利要求1-9中任一项所述的数据分析方法。
  13. 一种计算机可读介质，其中存储了如权利要求12所述的计算机程序。
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